Machine learning is basically about the science of giving computers the ability to learn & understand. AI & ML algorithms are being used daily in our lives through various significant applications such as self-driving cars, speech recognition, searches, and recommendations. And, also Machine learning is one of the most significant tech trends. It is true that Artificial intelligence and Machine learning algorithms are presently being used in as many kinds of software applications as possible.

Accurate or Quality Training data is paramount to the success of any AI, ML model or project. Just imagine If you train a model with poor-quality data, then how can you get proper results? Quality Training Data + Machine Learning = Proper & accurate results for any AI-based project.

The success of ML and AI models totally depend upon your Training Data 

To power Machine learning one of the basic requirements is DATA LABELING SERVICES, 

We use Advance Data labeling & Data Annotation Techniques that improve the quality of training data in an interactive manner after human correction takes Less time and greater output. Nothing is more essential than quality data in Machine Learning algorithms 

Basically, Data annotation is the process of detecting and tagging unstructured data to structured datasets for Machine Learning algorithms. The labeling process is both manual and assisted by software. So, Data annotation services are used when constructing Machine learning algorithms for major industries like autonomous vehicles, healthcare, finance, entertainment, e-commerce space, cybersecurity, agriculture etc. 

Data Annotation is very important for Machine learning algorithms and Artificial intelligence projects, and both have added immense value to the world.

To continue growing the AI industry, data annotation is a very necessary step. Also, Data annotation is already growing and will only continue to grow as more and more datasets are required for ML algorithms. 

So, concluding the article with an interesting stat about machine learning:
Machine learning is predicted to grow by 48% in the automotive industry.